Knowledge, Attitude, Usage of Artificial Intelligence; and Adaptability among Graduate Student

Abstract

This study examined the influence of knowledge, attitude, and usage of artificial intelligence (AI) on students’ adaptability. It specifically assessed AI-related knowledge in homework assistance, student engagement, and assessment accuracy; students’ attitudes in terms of awareness, understanding, and familiarity; and AI usage across functionality, availability, and complexity. Predictive correlational research designs were employed with participants selected from a higher education institution. Data were gathered using validated and reliable survey instruments and analyzed using descriptive statistics, Pearson product-moment correlation, and multiple regression analysis to determine the significant relationships and predictors of adaptability. Results revealed moderate levels of AI knowledge, usage, and adaptability, alongside a high level of positive attitude toward AI. Significant positive relationships were found between adaptability and all AI dimensions, indicating that stronger engagement, familiarity, access, and effective utilization of AI tools are associated with better adaptability. Regression analysis identified familiarity, availability, complexity management, and student engagement as significant predictors of adaptability, while awareness alone did not necessarily translate into improved results without practical competence. The study concludes that meaningful interaction, guided usage, and hands-on experience with AI significantly enhance students’ adaptability. It is recommended that higher education institutions implement structured AI literacy programs, provide continuous training and institutional support, and integrate AI tools strategically into instruction to maximize their educational benefits.